View Program - 63rd Annual Drosophila Research Conference

Atrial fibrillation (AF), the most common heart rhythm disorder, is reaching epidemic proportions in the aging population. In both human and model systems, it is not understood how aging, genetic predispositions, and external environmental factors synergize to promote arrhythmia, nor which gene regulatory networks initiate and maintain AF. Over 200 genetic variants have been associated with increased AF susceptibility, suggesting that the underlying cause is multifactorial, involving networks of interacting genes. Resolving complex interactions modulating cardiac function in AF is difficult in mammalian systems, but approachable using Drosophila. We utilize a multi-platform approach encompassing the genetically tractable Drosophila cardiac-aging model and hIPSC-atrial-like cardiomyocyte (ACM) model. The fly model allows for high-throughput quantification of aging effects in conjunction with genetic insults, whereas the ACM model allows for high-throughput combinatorial gene knockdown (KD). High-speed imaging of ACMs and fly hearts permit quantification of cardiac parameters such as action potential duration and arrhythmicity in ACMs, as well as contraction intervals and arrhythmicity in flies. Preliminary screens of candidate AF genes in both platforms have identified a network of seven corroborating hits. Network analysis has linked these 7 genes to ion channels, such as atrial-specific K+ channel Shaker (Sh), transcription factors Dorsocross (Doc) and Pannier (Pnr), as well as structural components such as Sarcolamban (SclA). Single genetic insults rarely produce robust arrhythmicity in our models, but we do see arrhythmia when testing interactions between genes in our network. Aging and pharmacological stressors (isoproterenol in ACMs, octopamine in flies) also interact with genetic insults to cause arrythmia. For example, KD of Doc in a Sh heterozygote background produces robust arrhythmicity, even at younger ages, whereas knockdown of SclA in a Sh mutant background mitigates cardiac alterations. Our approach has been validated in an atrial-specific double knockout mouse model of Doc and Sh, where atrial P-waves were deleted and QRS complex was broadened, both signatures of AF. Further identification and characterization of components from this Shaker-centric AF network across multiple platforms will not only improve our genetic and molecular understanding of AF pathogenesis but also guide novel experimental and therapeutic strategies to treat AF.

A multi-model system approach identifies genetic interactions underlying atrial fibrillation susceptibility